On the public citation graph

Development of a Convective–Diffusion Physics-Informed Neural Network for Thermal Analysis of Lithium Film Flow on the Surface of a Tokamak

0 signed · 28 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/nme.2579openalex-snapshot
Gmsh: A 3‐D finite element mesh generator with built‐in pre‐ and post‐processing facilities
inferredcites →https://doi.org/10.1007/s11431-022-2118-9openalex-snapshot
Multi-domain physics-informed neural network for solving heat conduction and conjugate natural convection with discontinuity of temperature gradient on interface
inferredcites →https://doi.org/10.1007/s11771-019-4244-yopenalex-snapshot
Analytical solutions of transient heat conduction in multilayered slabs and application to thermal analysis of landfills
inferredcites →https://doi.org/10.1016/0375-9601(92)90904-zopenalex-snapshot
The nonclassical method is more general than the direct method for symmetry reductions. An example of the Fitzhugh-Nagumo equation
inferredcites →https://doi.org/10.1016/j.amc.2006.07.002openalex-snapshot
The extended tanh method for new solitons solutions for many forms of the fifth-order KdV equations
inferredcites →https://doi.org/10.1016/j.anucene.2025.111960openalex-snapshot
Development of a Parametric Multi-Material Physics-Informed Neural Network for real-time heat transfer prediction in spherical tokamak divertor under transient heat loads
inferredcites →https://doi.org/10.1016/j.apm.2021.06.015openalex-snapshot
3D elastic dental analysis by a local RBF collocation method
inferredcites →https://doi.org/10.1016/j.cma.2021.113951openalex-snapshot
Variational phase-field fracture modeling with interfaces
inferredcites →https://doi.org/10.1016/j.enganabound.2022.01.003openalex-snapshot
Simulation of electromagnetic wave propagations in negative index materials by the localized RBF-collocation method
inferredcites →https://doi.org/10.1016/j.engappai.2021.104232openalex-snapshot
A physics-informed machine learning approach for solving heat transfer equation in advanced manufacturing and engineering applications
inferredcites →https://doi.org/10.1016/j.engfracmech.2022.108649openalex-snapshot
Fracture characterization from noisy displacement data using artificial neural networks
inferredcites →https://doi.org/10.1016/j.fusengdes.2021.112930openalex-snapshot
Design window for open-surface lithium divertor with helium-cooled substrate
inferredcites →https://doi.org/10.1016/j.fusengdes.2025.115036openalex-snapshot
A multi-domain physics-informed neural network for transient thermal analysis of a Tokamak divertor
inferredcites →https://doi.org/10.1016/j.icheatmasstransfer.2023.106662openalex-snapshot
Enhanced surrogate modelling of heat conduction problems using physics-informed neural network framework
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2003.09.011openalex-snapshot
On transient heat conduction in a one-dimensional composite slab
inferredcites →https://doi.org/10.1016/j.ijheatmasstransfer.2023.125089openalex-snapshot
Physics-informed neural networks for heat transfer prediction in two-phase flows
inferredcites →https://doi.org/10.1016/j.jcp.2020.109268openalex-snapshot
A meshless collocation method for band structure simulation of nanoscale phononic crystals based on nonlocal elasticity theory
inferredcites →https://doi.org/10.1016/j.jrmge.2022.01.010openalex-snapshot
Challenges associated with numerical back analysis in rock mechanics
inferredcites →https://doi.org/10.1016/j.net.2024.07.048openalex-snapshot
Leveraging physics-informed neural computing for transport simulations of nuclear fusion plasmas
inferredcites →https://doi.org/10.1016/j.taml.2020.01.039openalex-snapshot
Physics-informed deep learning for incompressible laminar flows
inferredcites →https://doi.org/10.1063/5.0116038openalex-snapshot
Multi-domain physics-informed neural network for solving forward and inverse problems of steady-state heat conduction in multilayer media
inferredcites →https://doi.org/10.1080/01691864.2017.1365009openalex-snapshot
Deep learning in robotics: a review of recent research
inferredcites →https://doi.org/10.1515/kern-2024-0077openalex-snapshot
Transient thermal analysis for optimal armor material in upgraded mockup for PST using MOOSE Framework
inferredcites →https://doi.org/10.33564/ijeast.2020.v04i12.054openalex-snapshot
ACTIVATION FUNCTIONS IN NEURAL NETWORKS
inferredcites →https://doi.org/10.3390/electronics10162029openalex-snapshot
Learning-Rate Annealing Methods for Deep Neural Networks
inferredcites →https://doi.org/10.3390/en16124799openalex-snapshot
Heat Transfer in the Components of Power Boilers and Related Technological and Endurance Problems
inferredcites →https://doi.org/10.3390/en17153652openalex-snapshot
Convective Heat Transfer in PWR, BWR, CANDU, SMR, and MSR Nuclear Reactors—A Review
inferredcites →https://doi.org/10.5815/ijieeb.2012.01.07openalex-snapshot
Application of Data Mining Techniques in Weather Prediction and Climate Change Studies
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.